Teaching

As a research student at the Department of Computer Science and Technology, I am involved in teaching and other academic activities such as Designing Coursework, Lab Demonstrations and Supervisions.

Supervisions


  • Interaction Design (Easter 2019, 2020): Supervision sessions are organised for small groups (2-5 students), for students to dig deeper into the course material and focus on doubt-clearing and discussions for individual work and progress of each student. Interaction Design supervisions focus on topics like Requirement Elicitation, Data Gathering Techniques, Prototyping and UX Design.

Teaching Assistant and Lab Demonstrator


  • Mobile Robot Systems (Lent 2019, 2020): MRS teaches the foundations of autonomous mobile robots, covering topics such as perception, motion control, and planning. It also teaches algorithmic strategies that enable the coordination of multi-robot systems and robot swarms.
    KRAs include:
    • Lab assistance with practical assignments for undergraduate and graduate students.
    • Coursework and project assistance with Multi-robot path planning assignments with the TurtleBot using ROS.

  • Interaction Design (Easter 2019, 2020): This course provides an introduction to interaction design, with an emphasis on understanding and experiencing the user interface design process from requirements and data gathering to implementation and evaluation, while gaining an understanding of the background to human factors. This course focuses equally on design and implementation.
    KRAs include:
    • Lab assistance with practical assignments for undergraduate and graduate students.
    • Coursework and project assistance with Designing and Prototyping assignments focussing on User Experience Design.

  • Affective Computing (Lent 2020): This module aims to impart knowledge and ability needed to make informed choices of models, data, and techniques for sensing, recognition, and expression of human affective and social behaviour (e.g., smile, frown, head nodding/shaking, agreement/disagreement), and its use in the design of innovative interactive technology (e.g., interaction with virtual agents, robots, and games; single and multi-user smart environments, e.g., in a car; implicit (multimedia) tagging; clinical and biomedical studies, e.g., autism, depression, pain).
    KRAs include:
    • Assistance with practical assignments on using Machine Learning for Affective Computing.
    • Coursework and project assistance for ACS (Master's level) mini-projects on Affective Comuting.